DEGRADATION ANALYSIS OF PROBABILISTIC PARALLEL CHOICE SYSTEMS

Degradation Analysis of Probabilistic Parallel Choice Systems

Degradation analysis is used to analyze the useful lifetimes of systems, their failure rates, and various other system parameters like mean time to failure (MTTF), mean time between failures (MTBF), and the system failure rate (SFR). In many systems, certain possible parallel paths of execution that have greater chances of success are preferred over others. Thus we introduce here the concept of...

On the Power of Probabilistic Choice in Synchronous Parallel Computations

Analysis of Probabilistic Basic Parallel Processes

Basic Parallel Processes (BPPs) are a well-known subclass of Petri Nets. They are the simplest common model of concurrent programs that allows unbounded spawning of processes. In the probabilistic version of BPPs, every process generates other processes according to a probability distribution. We study the decidability and complexity of fundamental qualitative problems over probabilistic BPPs —...

Parallel and Distributed Systems for Probabilistic Reasoning

Scalable probabilistic reasoning is the key to unlocking the full potential of the age of big data. From untangling the biological processes that govern cancer to effectively targeting products and advertisements, probabilistic reasoning is how we make sense of noisy data and turn information into understanding and action. Unfortunately, the algorithms and tools for sophisticated structured pro...

Coalgebraic analysis of probabilistic systems

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